Lecture notes in civil engineering, Год журнала: 2024, Номер unknown, С. 349 - 357
Опубликована: Дек. 31, 2024
Язык: Английский
Lecture notes in civil engineering, Год журнала: 2024, Номер unknown, С. 349 - 357
Опубликована: Дек. 31, 2024
Язык: Английский
Materials Today Communications, Год журнала: 2025, Номер unknown, С. 111706 - 111706
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Multiscale and Multidisciplinary Modeling Experiments and Design, Год журнала: 2025, Номер 8(2)
Опубликована: Янв. 30, 2025
Язык: Английский
Процитировано
0Scientific Reports, Год журнала: 2025, Номер 15(1)
Опубликована: Март 19, 2025
The use of plastic in concrete through various substitution approaches have been targeted last few decades with the main aim plummeting environmental loads construction industry. Although major mechanical and durability properties aggregate studied depth, petite data is available for its creep characteristics. Therefore, current study was designed to access recovery processed aggregates concretes. Five mixes consisting at replacement levels 0%, 25%, 50%, 75% 100% were developed w/c 0.5. tests conducted on all specimens determine evaluate a period approx. three years. augmentation resulted amplification instantaneous strain, ultimate shrinkage strain concrete. An increase 100, 119 69% noted total substitution. increased by 30.1, 96.8% 25% respectively. Overall it noticed that decrease compressive strength strains as compared reference mix. results from this experimental advocate specifically non-structural application requiring flexible solution.
Язык: Английский
Процитировано
0Journal of Building Engineering, Год журнала: 2025, Номер unknown, С. 112962 - 112962
Опубликована: Май 1, 2025
Язык: Английский
Процитировано
0Construction and Building Materials, Год журнала: 2025, Номер 486, С. 141962 - 141962
Опубликована: Май 29, 2025
Язык: Английский
Процитировано
0Buildings, Год журнала: 2025, Номер 15(11), С. 1942 - 1942
Опубликована: Июнь 4, 2025
This study demonstrates the conversion of agricultural and industrial waste into construction materials by developing ultra-high-performance concrete using cold-bonded sesame ash glass aggregates. The primary focus this was sustainability valorization in self-curing systems. focuses on many aspects producing cementless with superior short- long-term properties, incorporating an innovative artificial aggregate premanufactured glass. Prepacking technology casting used. A additive is used to reduce energy required for curing. In aggregates (CBAs), content ranged from 10 50% total sand volume. Polyethylene glycol as internal curing agent evaluate mechanical properties concrete, including compressive strength tensile at different ages. durability characteristics were also analyzed terms its resistance sulfates, chloride ion penetration, performance elevated temperatures 300 600 °C. Microscopic analyses conducted scanning electron microscopy (SEM), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FTIR), Differential Scanning Calorimetry (DSC). results showed a significant improvement performance, especially 30%, which resulted highest 147.2 MPa 90 days. 11.93% increase compared that reference mix. improved 14.5% same replacement ratio. mix containing 30% manufactured demonstrated best thermal resistance, retaining percentage residual both °C °C, well sulfate impact reduction factor 39.5%. When ratio increased 50%, penetration significantly 41% FTIR, TGA, DSC enhanced silicate polymerization carbonate formation, contributing chemical stability density matrix.
Язык: Английский
Процитировано
0Asian Journal of Civil Engineering, Год журнала: 2024, Номер unknown
Опубликована: Окт. 17, 2024
Язык: Английский
Процитировано
1Journal of Environmental Management, Год журнала: 2024, Номер 372, С. 123364 - 123364
Опубликована: Ноя. 16, 2024
Язык: Английский
Процитировано
1Research Square (Research Square), Год журнала: 2024, Номер unknown
Опубликована: Авг. 28, 2024
Язык: Английский
Процитировано
0Buildings, Год журнала: 2024, Номер 14(9), С. 2693 - 2693
Опубликована: Авг. 28, 2024
This research provides a comparative analysis of the optimization ultra-high-performance concrete (UHPC) using artificial neural network (ANN) and response surface methodology (RSM). By ANN RSM, yield UHPC was modeled optimized as function 22 independent variables, including cement content, compressive strength, type, strength class, fly-ash, slag, silica-fume, nano-silica, limestone powder, sand, coarse aggregates, maximum aggregate size, quartz water, super-plasticizers, polystyrene fiber, fiber diameter, length, steel curing time. Two statistical parameters were examined based on their modeling, i.e., determination coefficient (R2) mean square error (MSE). RSM evaluated for predictive generalization capabilities different dataset from previously published research. Results show that is computationally efficient easy to interpret, whereas more accurate at predicting characteristics due its nonlinear interactions. model (R = 0.95 R2 0.91) 0.94, 0.90) can predict strength. The prediction optimal an 3.5% 7%, respectively. According model’s sensitivity analysis, water have significant impact
Язык: Английский
Процитировано
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